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Objectives Many current jobs are characterized by sedentary behavior (SB) and lack of physical activity (PA). This review addresses the effectiveness of workplace interventions that are implemented during productive work and are intended to change workers' SB and/or PA. Methods We searched Scopus for articles published from 1992 until 12 March 2015. Relevant studies were evaluated using the Quality Assessment Tool for Quantitative Studies and summarized in a best-evidence synthesis. Primary outcomes were SB and PA, both at work and overall (ie, during the whole day); work performance and health-related parameters were secondary outcomes. Results The review included 40 studies describing 41 interventions organized into three categories: alternative workstations (20), interventions promoting stair use (11), and personalized behavioral interventions (10). Alternative workstations were found to decrease overall SB (strong evidence; even for treadmills separately); interventions promoting stair use were found to increase PA at work while personalized behavioral interventions increased overall PA (both with moderate evidence). There was moderate evidence to show alternative workstations influenced neither hemodynamics nor cardiorespiratory fitness and personalized behavioral interventions did not influence anthropometrie measures. Evidence was either insufficient or conflicting for intervention effects on work performance and lipid and metabolic profiles. Conclusions Current evidence suggests that some of the reviewed workplace interventions that are compatible with productive work indeed have positive effects on SB or PA at work. In addition, some of the interventions were found to influence overall SB or PA positively. Putative long-term effects remain to be established.

Remote work is a forced measure introduced by employers in order to prevent a viral infection. For employees, there are pluses in remote work - saving time and money on the road and high labour productivity because nothing distracts. There is a separate issue of information security for the employer when organising such a work regime for their employees. Any use of materials is allowed only with a hyperlink. Nowadays, in the realities of distance work, information security is coming first. Employees send all the information online; they use their data and send confidential information. Protection of personal data becomes a crucial point. The article deals with problems of ensuring information security in the field of remote work. The problems of information security during restrictive actions in connection with the coronavirus pandemic and the transfer of personnel to remote work are discussed. The threat of information leaks through remote workers is relatively high since the specialists responsible for the organisation’s information security do not have the opportunity to apply the entire arsenal of technical means and policies, with the help of which security is ensured at workstations in the office. Information leakage will lead to severe problems, so it is essential to consider what means you can use to ensure the company’s information security.

Alzheimer’s disease, as a most prevalent type of dementia, is quickly becoming one of the most expensive, lethal, and burdening diseases of this century. Though there are still no efficient therapies, early diagnosis and intervention are important directive significance to clinical works. Here, we develop a portable electrochemical micro-workstation platform consisting of an electrochemical micro-workstation and integrated electrochemical microarray for simultaneously detecting multiple AD biomarkers including Aβ40, Aβ42, T-tau, and P-tau181 in serum. The integrated electrochemical microarray is mainly used for droplet sample manipulation and signal generation. The micro-workstation can regulate signals and transfer the signals to a smartphone by Bluetooth embedded inside. This portable electrochemical micro-workstation platform exhibits excellent analysis performance. The LODs for Aβ40, Aβ42, T-tau, and P-tau181 are 0.125 pg/mL, 0.089 pg/mL, 0.142 pg/mL, and 0.176 pg/mL, respectively, which satisfies the needs of detecting AD biomarkers in serum. The combination of portable micro-workstation and integrated electrochemical microarray provides a promising strategy for the early diagnosis of Alzheimer’s disease and personal healthcare. Graphical abstract

Mean field games (MFG) and mean field control (MFC) are critical classes of multiagent models for the efficient analysis of massive populations of interacting agents. Their areas of application span topics in economics, finance, game theory, industrial engineering, crowd motion, and more. In this paper, we provide a flexible machine learning framework for the numerical solution of potential MFG and MFC models. State-of-the-art numerical methods for solving such problems utilize spatial discretization that leads to a curse of dimensionality. We approximately solve high-dimensional problems by combining Lagrangian and Eulerian viewpoints and leveraging recent advances from machine learning. More precisely, we work with a Lagrangian formulation of the problem and enforce the underlying Hamilton– Jacobi–Bellman (HJB) equation that is derived from the Eulerian formulation. Finally, a tailored neural network parameterization of the MFG/MFC solution helps us avoid any spatial discretization. Our numerical results include the approximate solution of 100-dimensional instances of optimal transport and crowd motion problems on a standard work station and a validation using a Eulerian solver in two dimensions. These results open the door to much-anticipated applications of MFG and MFC models that are beyond reach with existing numerical methods.

To address the issue that native scheduler in kubernetes cannot realize load balancing and cannot give full play to the overall performance of the cluster, we put forward a scheduling strategy based on Docker cluster of self-define kubernetes scheduler. The kubernetes scheduler can improve the native kubernetes scheduling strategy using optimized predicate algorithm model and priority algorithm model. Moreover, it can also be used to conduct contrast experiment between the native scheduling strategy of kubernetes and that of self-define kubernetes scheduler. It is in VMware Workstation environment where Centos system is installed, and where Docker container service and kubernetes container orchestration engine are deployed to establish Docker container cluster. Experimental results show that cluster scheduling strategy of the self-define kubernetes scheduler is better than the native one, because it can save more system resources to improve the fairness of the cluster scheduling and the scheduling efficiency.

Despite the high automatization that characterizes modern production, human operators still hold a vital position in manufacturing, which should be reinforced in the transition to the era of Industry 4.0. As human operators may support increased flexibility and adaptability to their tasks, they gain an advantage in highly customized productions, where products’ configuration and tasks allocated per workstation may be dynamically changed. In order to support dynamic knowledge transfer to the human operators in a way that is perceivable and does not limit operators’ capabilities, it is important to exploit novel visualization technologies introduced by Industry 4.0. This paper presents an automated approach for remotely supporting assembly workstations, with human operators using augmented reality technology. The system retrieves the workstation’s schedule and automatically generates assembly instructions, utilizing information from the product’s design, enriched with order-specific annotations based on product customization. Then, the generated augmented reality instructions are transmitted through a cloud environment to the assembly station operator, aiming to support dynamic production re-scheduling. The developed system is validated in a real-life case study provided by the automotive industry.

The new facility has 30 workstations that operate in the manner of a private dental practice. Students can practice any dental procedure from a routine cleaning to a root canal on mannequins.

Manufacturing flexibility improves a firm’s ability to react in timely manner to customer demands and to increase production system productivity without incurring excessive costs and expending an excessive amount of resources. The emerging technologies in the Industry 4.0 era, such as cloud operations or industrial Artificial Intelligence, allow for new flexible production systems. We develop and test an analytical model for a throughput analysis and use it to reveal the conditions under which the autonomous mobile robots (AMR)-based flexible production networks are more advantageous as compared to the traditional production lines. Using a circular loop among workstations and inter-operational buffers, our model allows congestion to be avoided by utilizing multiple crosses and analyzing both the flow and the load/unload phases. The sensitivity analysis shows that the cost of the AMRs and the number of shifts are the key factors in improving flexibility and productivity. The outcomes of this research promote a deeper understanding of the role of AMRs in Industry 4.0-based production networks and can be utilized by production planners to determine optimal configurations and the associated performance impact of the AMR-based production networks in as compared to the traditionally balanced lines. This study supports the decision-makers in how the AMR in production systems in process industry can improve manufacturing performance in terms of productivity, flexibility, and costs.

Purpose The purpose of this paper is to identify the non-value-adding activities (NVAs) of core making process and to eliminate them through the standardization-of-work (SW) procedures in a manufacturing company. Design/methodology/approach The action-research methodology was adopted for the current study. First, various lean tools were identified through literature review, and the bottleneck area was identified in discussion with the shop-floor executives. NVAs were recorded after a continuous process study including method study and motion analysis followed by the standard operating procedure. Second, the standardized work combination tables were prepared and NVAs were eliminated using the SW procedures. SW has been opted because it is a set of actions which helps in analyzing, improving and controlling the process and it leads to continual improvement. Findings The production logbook revealed that the capacity in this particular workstation was 54 pieces per 7 h work shift against the current production of approx. 45–50 pieces (past data). SW saved 31.6 s per cycle which boosted the production up to 58 pieces per 7 h work shift. Finally, the authors came to know that the productivity of this particular process increased up to 6.5 percent which may upsurge if this action is executed continually with the support from shop-floor executives and management. These results were also compared with previous research works in this area and found significant relevance, and hence, the results appear to be reliable. Research limitations/implications This is a unique study in itself which explores the lean model by assessing NVAs of core making process. The proposed approach needs to be tested across different other core making processes of the case company so as to generalize the effectiveness of SW as well as the results obtained in the current study. Practical implications The current study illustrates an important step to give more visibility to the lean concept by addressing the problem of lack of standard procedures. This study will help the shop-floor executives and managers to focus their efforts in achieving high performance through effective implementation of SW. The study should be of the interest of researchers in the area of lean manufacturing, operations management, productivity analysis, etc. Originality/value The findings of this study are based on the problem formulation for productivity gains using SW procedures in the case company. The study introduces a new perspective for the execution of SW for core making processes. SW created transparency in workflow, enhanced the safety and eliminated the 3Ms. The outcome of the current study was discussed with the production team and management of the company to validate the productivity gains and received an optimistic response. Most importantly, these improvements were achieved with no investment in machinery or tooling.